1. Field of the Invention
The present invention provides systems, methods, and devices for improved computed tomography (CT). More specifically, the present invention includes methods for improved cone-beam computed tomography (CBCT) resolution using improved filtered back projection (FBP) algorithms, which can be used for cardiac tomography and across other tomographic modalities.
2. Description of Related Art
Cardiovascular diseases (CVDs) are pervasive (American Heart Association 2004). CVD is the number one killer in the western world. The cost of the health care for CVD is skyrocketing. In 2004, the estimated direct and indirect cost of CVD was $368.4 billion.
Coronary artery disease is a leading cause of death as a result of a myocardial infarct (heart attack) without any symptom. Tomographic equipment with high temporal resolution is needed in order to successfully perform a cardiac scan and understand the etiology and pathogenesis of CVD, such as high blood pressure, coronary artery diseases, congestive heart failure, stroke and congenital cardiovascular defects, as well as to develop effective prevention and treatment strategies. CT scanners are now considered instrumental for detecting early heart diseases and are a centerpiece of preventive cardiology programs.
Although there has been an explosive growth in the development of CT scanners for cardiac CT studies, the efforts are generally limited to regular heartbeats. When applying traditional CT algorithms for cardiac CT reconstruction, the cardiac images may be inaccurate or useless based on substantial motion blurring, especially seen in patients who have high and irregular heartbeats due to the fact that each projection sector covers a projection angular range of a substantial length. Within such an angular range, the heart moves appreciably, especially when it is not in a relative stationary phase. As a benchmark, a ˜0.3 mm spatial resolution is routinely achieved in spiral CT of the temporal bone where the motion magnitude is much less than that of the heart (see M. Vannier and G. Wang, Spiral C T refines imaging of temporal bone disorders, Diagnostic imaging, vol. 15, p. 116-121, 1993 and G. Wang, et al., Design, analysis and simulation for development of the first clinical micro-CT scanner1, Academic Radiology, vol. 12, pp. 511-525, 2005, which is incorporated by reference herein in its entirety). Spatial resolution with cardiac CT is at best in the millimeter domain.
Over the last thirty years, computer tomography (CT) has gone from image reconstruction based on scanning in a slice-by-slice process to spiral scanning. From the mid-1980s to present day, spiral type scanning has become the preferred process for data collection in CT. Under spiral scanning, a table with the patient continuously moves through the gantry while the source in the gantry is continuously rotating about the table. At first, spiral scanning used a one-dimensional detector array, which received data in one dimension (a single row of detectors). Later, two-dimensional detectors, where multiple rows (two or more rows) of detectors sit next to one another, were introduced. In CT there have been significant problems for image reconstruction especially for two-dimensional detectors.
For three/four-dimensional (also known as volumetric/dynamic) image reconstruction from the data provided by a spiral scan with two-dimensional detectors, known groups of algorithms include: exact algorithms, quasi-exact algorithms, approximate algorithms, and iterative algorithms. While the best approximate algorithms are of Feldkamp-type, the state of the art of the exact algorithms is the recently developed Katsevich algorithm.
Under ideal circumstances, exact algorithms can provide a replication of a true object from data acquired from a spiral scan. However, exact algorithms can require a larger detector array, more memory, are more sensitive to noise, and run slower than approximate algorithms. Approximate algorithms can produce an image very efficiently using less computing power than exact algorithms. However, even under typical circumstances they produce an approximate image that may be similar to but still different from the exact image. In particular, approximate algorithms can create artifacts, which are false features, in an image. Under certain circumstances these artifacts can be quite severe.
To perform the long object reconstruction with longitudinally truncated data, the spiral cone-beam scanning mode and a generalized Feldkamp-type algorithm were proposed by Wang and others in 1991. However, the earlier image reconstruction algorithms for that purpose are either approximate or exact only using data from multiple spiral turns.
In 2002, an exact and efficient method was developed by Katsevich, which is a significant breakthrough in the area of spiral cone-beam CT. The Katsevich algorithm is in a filtered-backprojection (FBP) format using data from a PI-arc (scanning arc corresponding to the PI-line and less than one turn) based on the so-called PI-line and the Tam-Danielsson window. The principle is that any point inside the standard spiral or helical belongs to one and only one PI-line. Any point on the PI-line can be reconstructed from filtered data on the detector plane with the angular parameter from the PI-arc. In 2003, a slow FBP and a backprojected-filtration algorithm (BPF) were developed for helical cone-beam CT based on the Katsevich algorithm by exchanging the order of integrals. For important biomedical applications including application with movement present such as cardiac CT, generalization of the exact cone-beam reconstruction algorithms from the case of standard spirals to the case of nonstandard spirals and other scanning loci is desirable and useful. Although the current Katsevich-type algorithms are known for a standard spiral scan, there are no known fast algorithms, systems, devices and methods that can reconstruct an image exactly or quasi-exactly from data acquired in a CT scan with good temporal resolution.
Therefore, despite the impressive advancement of the CT technology, there are still unmet, critical and immediate needs such as those mentioned above for better image quality in many cardiac and other CT investigations wherein the motion magnitude is increased.